Multivariate Response Surface Methodology Research Articles

Optimization of Oleogel Formulation for Curcumin Vehiculization and Lipid Oxidation Stability by Multi-response Surface Methodology

Curcumin is a natural polyphenolic compound with multiple properties such as anticancer, anti-inflammatory, antioxidant, antiviral, and cytoprotective action. It is expected that curcumin has the therapeutic potential to prevent diverse lifestyle-related diseases. However, curcumin is not readily soluble in water and presents low stability under light, heat and physiological pH conditions which, in addition, implies an extremely low level of bioavailability. On the other hand, oleogels are semisolid systems composed of a liquid phase that is physically entrapped by a structurant network, ultimately leading to the formation of a gel. The continuous phase consists of a hydrophobic liquid (e.g., an oil) where a self-assembled network (composed by the structurant) is responsible for the physical entrapment of the liquid. The structural conformation is always dependent on the type of structurant used, which will dictate the desired final application of the oleogels. In this work, the formulation of an oleogel specially designed to stabilize and transport curcumin and to protect the lipid phase –mainly composed of a fish oil concentrate– against oxidation processes has been optimized.To this end, a Box-Behnken Design was carried out to study the influence of the curcumin amount, the structurant concentration and the manufacturing temperature on the oxidation degree of the oleogelified lipid matrix and on the chemical stability of the curcumin transported by this system. The results were interpreted by using the multi-response surface methodology, obtaining the optimal oleogel formulation to minimize the lipid oxidation and maximize the content of vehiculized curcumin.The results show that the optimal oleogel formulation –for samples stored at 23 oC– was achieved for the following values of the variables studied: [Curc.] = 0.150 wt.%, [Struc.] = 4.461 wt.% and T = 64.63 oC. In contrast, for samples stored at 40 oC, the optimal formulation obtained changed slightly: [Curc.] = 0.150 wt.%, [Struc.] = 7.000 wt.% and T = 62.82 oC. Finally, results suggest that oleogels are interesting structured lipid systems to transport and protect bioactive compounds.

Struvite production from food processing wastewater and incinerated sewage sludge ash as an alternative N and P source: Optimization of multiple resources recovery by response surface methodology

Nitrogen (N) and phosphorus (P) cause eutrophication in water body, but they also act as an essential and limiting nutrient in agriculture. In this study food wastewater (FW) and incinerated sewage sludge ash (ISSA) were combined together as the alternative NH4+-N and PO43−-P sources to produce struvite. PO43−-P (67.0 g/kg SSA) was leached from the ISSA by acid and alkali treatment of ISSA. Multi-response surface methodology (RSM) has been applied to find the optimal condition for the maximal NH4+-N and PO43−-P recovery of 79.6% and 99.9%, respectively, from the mixed solution of ISSA leachate and centrifuged FW at pH 9.28, Mg/P 2, and N/P 0.6. Overall yields were 64.9% NH4+-N (27.1 g NH4+-N /L FW) and 72.7% PO43−-P (72.8 g T-P/kg ISSA) from the FW and ISSA, respectively. XRD, ICP-OES, and P-bioavailability analysis confirmed that the recovered precipitate had high struvite content (77.5%) and P-bioavailability (98.4%) with negligible heavy metals content. FW and ISSA were successfully combined together to produce struvite and it can be utilized as an effective fertilizer.

Multiresponse surface methodology to optimize the tablet’s quality characteristics

Response surface methodology is able to find the setting for input variables that optimize the response. When there is more than one response, the multiresponse surface methodology is used. To optimize these responses simultaneously, especially for quality characteristics, a hybrid method of Fuzzy Goal Programming (FGP) - Genetic Algorithm (GA) can accommodate it. In this research, the tablet’s quality characteristics are the level of hardness, the level of friability, and the disintegration time of the tablet. The input variables that are considered to have a significant effect on the quality characteristics of the tablet are levels of binding agents, disintegrants, and the ma-chine pressure on compression process. The use of FGP is based on the reason that this method provides flexibility especially when objective functions and constraints cannot be clearly defined, thus requiring fuzzy numbers as operators. This advantage is not owned by the basic method of common Goal Programming (GP). The use of GA is to find a global optimum solution because it implements a ran-dom system.

Coagulation: Determination of Key Operating Parameters by Multi-Response Surface Methodology Using Desirability Functions

The clarification process removes colloidal particles that are suspended in waste water. The efficiency of this process is influenced by a series of inputs or parameters of the coagulation process, of which the most commonly used are initial turbidity, natural coagulant dosage, temperature, mixing speed and mixing time. The estimation of the natural coagulant dosage that is required to effectively remove these total suspended solids is usually determined by a jar test. This test seeks to achieve the highest efficiency of removal of the total suspended solids while reducing the final turbidity of waste water. This is often configured in iterative fashion, and requires significant experimentation and coagulant. This paper seeks to identify regression models that relate the clarification process parameters to the process outputs (final turbidity and total suspend solid) by the Response Surface Methodology (RSM) based on experiments of Central Composite Design (CCD) of experiments that involve three emerging natural coagulants. Several clarification process scenarios also were proposed and demonstrated using the Multi-Response Surface (MRS) with desirability functions. The experimental results were found to be in close agreement to what are provided by the regression models. This validates the use of the MRS-based methodology to achieve satisfactory predictions after minimal experimentation.

Polyphenols-enriched Hibiscus sabdariffa extract-loaded nanostructured lipid carriers (NLC): Optimization by multi-response surface methodology

Nanoparticles are commonly used to improve the bioavailability of several bioactive compounds. In this work, nanostructured lipid carriers (NLC) have been optimized by response-surface methodology to protect phenolic compounds from Hibiscus sabdariffa. The influence of lipid and surfactant concentration on the mean particle size, polydispersity index and zeta potential of NLC was analysed. The results showed that the effect of both independent variables was statistically significant on the selected responses. The optimized formulation obtained from the predicted model was composed of 2.21% (w/w) of lipid phase and 1.93% (w/w) of surfactant, with a desirability function of 0.77. The loading of polyphenol-enriched Hibiscus sabdariffa extract - obtained by microwave assisted extraction or by pressurized liquid extraction - within the NLC resulted in particles with a mean size of 470 ± 8 nm (encapsulation efficiency of 52.9 ± 0.9% for quercetin and 60 ± 2% for anthocyanins) and 344 ± 12 nm (encapsulation efficiency of 93 ± 3% for quercetin and 84 ± 4% for anthocyanins), respectively. Transmission electron microscopy images and Fourier transformed infra-red analysis of extracts-loaded NLC confirmed that interaction between lipids and polyphenols improved the physicochemical stability of the particles. Our findings highlight the added value of NLC as a delivery system for phenolic compounds extracted from Hibiscus sabdariffa.

OPTIMIZATION OF ULTRASONIC-ASSISTED EXTRACTION PARAMETERS FOR ANTIOXIDANTS FROM Curcuma longa L.

In this study, ultrasonication was used to extract antioxidant compounds such as polyphenols, flavonoids, and curcuminoids from turmeric (Curcuma longa L.) The influences of time, ethanol concentration and temperature as three independent factors on the extraction of the total phenolic content were evaluated by the Folin-Ciocalteu method and the antioxidant capacities by the ABTS and chromium reducing antioxidant capacity (CHROMAC) methods. The central composite design (CCD) with a multi-response surface methodology (MRSM) was used for the statistical modeling of the response data followed by the regression and analysis of variance (ANOVA) to determine the significance of the model and the factors. The response predictions obtained at optimum extraction conditions of an extraction time of 64min, an ethanol concentration of 82% (v/v) and an extraction temperature of 32°C were 47.32mg GAE/g (for Folin-Ciocalteu), 29.15 (for ABTS) and 5.17mg TE/g (for CHROMAC). The predicted values obtained from the multi-response surface methodology agreed with the experimental values data 95% confidence level. These data indicate that the multi-response surface methodology is applicable for optimizing the ultrasonic-assisted extraction of antioxidant compounds from C. longa.

Microwave-assisted dispersive liquid-liquid microextraction coupling to solidification of floating organic droplet for colorants analysis in selected cosmetics by liquid chromatography

A convenient and rapid method was developed for determination of fourteen colorants in selected cosmetics based on microwave-assisted dispersive liquid-liquid microextraction (MA-DLLME) using solidification of the floating organic droplet (SFOD) as a clean-up step followed by high-performance liquid chromatography diode array detection (HPLC-DAD). DLLME was performed in a microwave device for reducing manual operations and facilitating rapid extraction equilibrium, resulting in high sample throughput and good extraction efficiency. Matrix effects could be effectively eliminated by SFOD technique. Various parameters affecting the extraction efficiency were optimized by multi-response surface methodology. The limits of detection and quantification were 0.25–3.2 mg kg−1 and 0.85–11.0 mg kg−1, respectively. The recoveries ranged from 90.2% to 106.1% with relative standard deviations of 0.30–3.1%. The method was successfully applied to the analysis of cosmetics, in which all the colorants could be quantified, and their median values ranged from 4.94 to 591 mg kg−1 for seventy-two lipsticks, and from 7.70 to 1.73 × 103 mg kg−1 for fifty eye shadows, respectively. The proposed protocol could achieve batch preparation of samples and avoid measurement errors from the obvious volume reduction of the recovered extract, and it could serve as a powerful tool for high-throughput analysis of multiple colorants in complex samples.

Optimization of Welding Parameters in Resistance Spot Welding of 980 MPa Grade GA Steel Sheet using Multi-Response Surface Methodology

In this study, the welding quality prediction model with high reliability was developed for the 980 MPa grade TRIP steel with minimum conditions in resistance spot welding process using response surface methodology. The welding time and welding current were selected as the important parameters. The welding quality was predicted by deriving four parameters including tensile shear strength, nugget size, expulsion, and button fracture. The experiment was carried out by using the central composite design. Then, the regression equation derived using the result data was analyzed and the effect of the independent variable on the objective function was analyzed by ANOVA. The welding time had a very small effect on tensile shear strength and nugget, but welding current had a dominant effect on the two properties. Also, the reliability of the derived regression mode l equation is verified by R correlation coefficient and experiments. Key words: Weldments, Resistance spot welding, Response surface methodology, GA steel, ANOVA

Determination of Pesticide Residues in Fruit and Vegetables by High-Performance Liquid Chromatography–Tandem Mass Spectrometry with Multivariate Response Surface Methodology

ABSTRACTMultivariate response surface methodology optimization using Placket–Burman and Box–Behnken designs were respectively used for the screening and optimization of significant factors for liquid chromatography–tandem mass spectrometry. Consequently, the optimized instrument successfully improved the sample preparation protocol and the method was validated. However, modified QuEChERS dispersive solid phase extraction coupled with ionic liquid-based dispersive liquid–liquid microextraction were used for the determination of multi-pesticide residues in fruit and vegetable samples. The analysed samples were jackfruit, strawberries, cucumber, pears, and carrots. The resulting linearity range (5–400 µg/kg) and regression coefficient (>0.99) results were satisfactory. The 94.2 and 95.8% accuracy (89–138%) and precision (0–25%) results were satisfactory and within the recommended ranges (≤20%) and (70–120%), respectively. The limits of detection (0.01–0.54 µg/kg) and quantitation (0.03–1.79 µg/kg) were excellent. The matrix effects (≤−87%) for all analysed samples were not significant. The estimated measurement uncertainties (≤27%) were within the acceptable range (≤50%). Justifiably, the response surface methodology optimized instrument and sample treatment techniques were reliable and convenient for multi-pesticide residue determination in various fruits and vegetables.

Multi-pesticide Residues Determination in Samples of Fruits and Vegetables Using Chemometrics Approach to QuEChERS-dSPE Coupled with Ionic Liquid-Based DLLME and LC–MS/MS

Pesticides play vital roles in agricultural practices, but the nature and mishandling of the chemicals have led to their accumulation in moist soil, vegetables and fruits. Thus, development of efficient methods for pesticides determination is one of the most important ways to address such challenges. Multivariate response surface methodology optimisation using Placket–Burman and Box–Behnken designs were respectively used for screening and optimisation of significant factors of quick, easy, cheap, effective, rugged and safe (QuEChERS) with dispersive solid-phase extraction (SPE). Consequently, the optimised QuEChERS-dSPE technique coupled with modified ionic liquid-based (IL-based) dispersive liquid–liquid microextraction was used for sample preparation before LC–MS/MS. The developed method was validated (SANTE 11831-2017) for multi-pesticide residues determination in samples of bananas, cabbages, tomatoes, oranges and onions. The precision results were satisfactory in terms of relative standard deviation (≤ 20%) as recommended. The results of accuracy for relative recoveries (82–137%) were satisfactory because 92.5% of results were within the recommended range (70–120%). The matrix effects in all the samples were very weak (less effective) (≤ − 80%). The linearity of the evaluated results was 5–400 µg kg−1 and regression coefficients (R2) were > 0.99. The resulting limits of detection and quantitation were 0.02–0.32 and 0.07–1.06 µg kg−1, respectively, and therefore satisfactory. Certifiably, the estimated measurement uncertainties range (1–16%) was acceptable (≤ 50%). Thus, the developed method could be reliable and suitable for routine determination of multiple pesticide residues in various vegetable and fruit samples.

Development and stability evaluation of water-in-edible oils emulsions formulated with the incorporation of hydrophilic Hibiscus sabdariffa extract

New functional oils (extra virgin olive oil, EVOO and sunflower oil, SO) containing antioxidants from Hibiscus sabdariffa extract were developed by W/O emulsion. Their physical and chemical stability was measured over time. The lowest coalescence rate was obtained with 8 and 12 wt% surfactant amount for EVOO and SO emulsions, respectively. Before the evaluation of the oxidative stability, an optimization of phenolic compounds extraction from emulsions by multi-response surface methodology was performed. EVOO emulsions were chemically more stable over time than SO emulsions in terms of total phenolic content (TPC), antioxidant activity and chemical composition measured by HPLC-ESI.TOF-MS. TPC significantly increased (from 2.02 ± 0.07 to 2.71 ± 0.06 mg Eq GAE/g extract) and the antioxidant activity measured by TEAC remained constant for 1 month of storage. Thus, W/O emulsion technology has proven to be a potential method to vehiculize and stabilize bioactive compounds from H. sabdariffa into edible oils.

Optimization of ultrasonic-assisted extraction via multiresponse surface for high antioxidant recovery from Chlorella vulgaris (Chlorophyta)

:The present study reports on the extraction of antioxidant compounds from Chlorella vulgaris. Multiresponse surface methodology coupled with a central composite design was used to optimize the independent parameters for ultrasonic-assisted extraction (UAE). Four independent parameters were optimized, including extraction time (15–155 min), ethanol volume (35–95%, v/v), extraction temperature (15–75°C) and liquid/solid ratio (30–150 ml g−1). Total phenolic content and antioxidant capacity [2,2′-azinobis(3-ethylbenzothiazoline-6-sulphonic acid) and chromium-reducing antiaoxidant capacity methods] were considered response parameters, whereas the effects of extraction time, ethanol volume, extraction temperature and liquid/solid ratio were studied. The optimal condition was obtained with an extraction time of 146 min, ethanol volume of 71% (v/v), extraction temperature of 72°C and liquid/solid ratio of 62 ml g−1 of sample. The experimental values agreed with predicted values within a 95% confidence level. This indicates that multiresponse surface methodology is suitable for optimizing UAE of antioxidant compounds from C. vulgaris.

Drilling process optimization by using fuzzy-based multi-response surface methodology

Drilling process optimization by using fuzzy-based multi-response surface methodology

An Improvement in Biodiesel Production from Waste Cooking Oil by Applying Thought Multi-Response Surface Methodology Using Desirability Functions

The exhaustion of natural resources has increased petroleum prices and the environmental impact of oil has stimulated the search for an alternative source of energy such as biodiesel. Waste cooking oil is a potential replacement for vegetable oils in the production of biodiesel. Biodiesel is synthesized by direct transesterification of vegetable oils, which is controlled by several inputs or process variables, including the dosage of catalyst, process temperature, mixing speed, mixing time, humidity and impurities of waste cooking oil that was studied in this case. Yield, turbidity, density, viscosity and higher heating value are considered as outputs. This paper used multi-response surface methodology (MRS) with desirability functions to find the best combination of input variables used in the transesterification reactions to improve the production of biodiesel. In this case, several biodiesel optimization scenarios have been proposed. They are based on a desire to improve the biodiesel yield and the higher heating value, while decreasing the viscosity, density and turbidity. The results demonstrated that, although waste cooking oil was collected from various sources, the dosage of catalyst is one of the most important variables in the yield of biodiesel production, whereas the viscosity obtained was similar in all samples of the biodiesel that was studied.

Synthesis, characterization and application of nanoscale zero-valent iron in the degradation of the azo dye Disperse Red 1

In this work, a multivariate response surface methodology (RSM), was applied to analyze the effects of the synthesis variables that affect the reactivity of nanosized zero valent iron particles (NZVI), obtained by chemical reduction with sodium borohidride on the decoloration of azo dye Disperse Red 1 (DR1). Statistical analysis and data interpretation revealed that the generated model showed significant regression and fitting. The conditions that generated NZVI with higher reactivity correspond to [Fe 2+]:[BH4−] molar ratio=1:3, higher rates of reducing agent addition and lower pH (2–3). NZVI particles synthesized under the optimal conditions were characterized via XRD, BET surface area and electron microscopy. The results showed that the nanostructured material had composition, morphology and crystallinity typical of zero-valent iron, with BET surface area of ​​45m2g−1 and an average particle size of 60nm. NZVI yielded high color removal in fairly short time (around 98% in 10min). Latter combination with H2O2 allowed high mineralization.

Optimization of microwave-assisted extraction and pressurized liquid extraction of phenolic compounds from Moringa oleifera leaves by multiresponse surface methodology.

This work aims at studying the optimization of microwave-assisted extraction (MAE) and pressurized liquid extraction (PLE) by multi-response surface methodology (RSM) to test their efficiency towards the extraction of phenolic compounds from Moringa oleifera (M. oleifera) leaves. The extraction yield, total phenolic content (TPC), total flavonoid content (TF), DPPH scavenging method and trolox equivalent antioxidant capacity (TEAC) assay were considered as response variables while effects of extraction time, percentage of ethanol, and temperature were studied. Extraction time of 20 min, 42% ethanol and 158°C were the MAE optimum conditions for achieving extraction yield of 26 ± 2%, EC50 15 ± 2 μg/mL, 16 ± 1 Eq Trolox/100 g dry leaf, 5.2 ± 0.5 mg Eq quercetin/g dry leaf, and 86 ± 4 mg GAE/g dry leaf. Regarding PLE, the optimum conditions that allowed extraction yield of 56 ± 2%, EC50 21 ± 3 μg/mL, 12 ± 2 mmol Eq Trolox/100 g dry leaf, 6.5 ± 0.2 mg Eq quercetin/g dry leaf, and 59 ± 6 mg GAE/g dry leaf were 128°C, 35% of ethanol, and 20 min. PLE enabled the extraction of phenolic compounds with a higher number of hydroxyl-type substituents such as kaempferol diglycoside and its acetyl derivatives and those that are sensitive to high temperatures (glucosinolates or amino acids) while MAE allowed better recoveries of kaempferol, quercetin, and their glucosides derivatives.

Degradation of hydroxycinnamic acid mixtures in aqueous sucrose solutions by the Fenton process.

The degradation efficiencies and behaviors of caffeic acid (CaA), p-coumaric acid (pCoA), and ferulic acid (FeA) in aqueous sucrose solutions containing the mixture of these hydroxycinnamic acids (HCAs) were studied by the Fenton oxidation process. Central composite design and multiresponse surface methodology were used to evaluate and optimize the interactive effects of process parameters. Four quadratic polynomial models were developed for the degradation of each individual acid in the mixture and the total HCAs degraded. Sucrose was the most influential parameter that significantly affected the total amount of HCA degraded. Under the conditions studied there was a <0.01% loss of sucrose in all reactions. The optimal values of the process parameters for a 200 mg/L HCA mixture in water (pH 4.73, 25.15 °C) and sucrose solution (13 mass %, pH 5.39, 35.98 °C) were 77% and 57%, respectively. Regression analysis showed goodness of fit between the experimental results and the predicted values. The degradation behavior of CaA differed from those of pCoA and FeA, where further CaA degradation is observed at increasing sucrose and decreasing solution pH. The differences (established using UV/vis and ATR-FTIR spectroscopy) were because, unlike the other acids, CaA formed a complex with Fe(III) or with Fe(III) hydrogen-bonded to sucrose and coprecipitated with lepidocrocite, an iron oxyhydroxide.

Asymptotic normality of the optimal solution in multiresponse surface mathematical programming

An explicit form for the perturbation effect on the matrix of regression coefficients on the optimal solution in multiresponse surface methodology is obtained in this paper. Then, the sensitivity analysis of the optimal solution is studied and the critical point characterisation of the convex program, associated with the optimum of a multiresponse surface, is also analysed. Finally, the asymptotic normality of the optimal solution is derived by the standard methods.

Multivariate analysis of mainstream tobacco smoke particulate phase by headspace solid-phase micro extraction coupled with comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry

A method involving headspace solid-phase microextraction (HS-SPME) and comprehensive two-dimensional gas chromatography (GC×GC) coupled to time-of-flight mass spectrometry (TOFMS) was developed and applied to evaluate profiles of volatile compounds present in mainstream tobacco smoke particulate matter trapped on glass fiber filters. Six SPME fibers were tested for the extraction capacities toward selected compounds, showing the best results for the polyacrylate fiber. The optimization of the extraction conditions was carried out using multivariate response surface methodology. Two cigarette types differing in a filter design were analyzed using optimized conditions. A template was built in order to generate comprehensive chemical information, which conceded obtaining consistent information across 24 chromatograms. Principal component analysis (PCA) allowed a clear differentiation of the studied cigarette types. Fisher ratio analysis allowed identification of compounds responsible for the chemical differences between the cigarette samples. Of the selected 143 most important ones, 134 analytes were reduced by the active carbon filter, while for nine, classical cellulose acetate filter was more efficient.

Optimal design of the auto parts supply chain for JIT operations: Sequential bifurcation factor screening and multi-response surface methodology

This research proposes a solution framework based on discrete-event simulation, sequential bifurcation (SB) and response surface methodology (RSM) to address a multi-response optimization problem inherent in an auto parts supply chain. The objective is to identify the most efficient operating setting that would maximize the logistics performance after the expansion of the assembly plant’s capacity due to market growth. In the proposed framework, we first construct a comprehensive simulation as a platform to model the physical flow of the auto parts operations. We then apply the SB to identify the most important factors that influence system performance. To determine the optimal levels of these key factors, we employ RSM to develop metamodels that best describe the relationship between key decision variables and the multiple system responses. We adapt the Derringer–Suich’s desirability function to find the optimal solution of the metamodels. Computational study shows that our method enables the greatest improvement on system performance. The proposed method helps the case firm develop insights into system dynamics and to optimize the operating condition. It realizes the performance objective of the auto parts supply chain without the need for additional fiscal investment.